Use of digital cameras for phenological observations

Vegetation phenology such as the onset of green-up and senescence is strongly controlled by climate and other environmental factors, and in turn affects the terrestrial carbon balance. Therefore, phenological observation is important as an indicator of global warming and for estimation of the terrestrial carbon balance. Because phenological responses differ from species to species, precise monitoring from the species scale to the global scale is required. In this study, we analyzed images from digital cameras, which have proliferated in recent years, to investigate their utility as remote sensors. We collected daily images taken by digital cameras in national parks across Japan over 8 years in wetland mixed deciduous forest, and evergreen broadleaved forest. Values of red, green, and blue (RGB) channels in each pixel within images were extracted, and a vegetation green excess index (2G-RBi) was calculated to detect phenology. The time series of 2G-RBi showed clear phenological patterns of each vegetation type in each year at the species or community scale. Even physiological damage due to a typhoon was detected. The dates of green-up were estimated easily and objectively from the second derivative of 2G-RBi, and a trend in yearly green-up dates of various types of vegetation was demonstrated. Furthermore, a strong correlation between interannual variations in green-up dates and local spring temperature was found, and the sensitivity of green-up date to temperature was revealed. The results suggest the utility of digital cameras for phenological observations at precise temporal and spatial resolutions, despite a year-to-year drift of color balance of camera as a technical device. As a form of near-surface remote sensing, digital cameras could obtain significant ecological information. Establishing camera networks could help us understand phenological responses at a wide range of scales.     

Demography of an endangered endemic rupicolous cactus

The snow cover extent is an important factor for the structure and composition of arctic and alpine tundra communities. Over the last few decades, snowmelt in many arctic and alpine regions has advanced, causing the growing season to start earlier and last longer. In a field experiment in subarctic tundra in Interior Alaska, I manipulated the timing of snowmelt and measured the response in mortality, phenology, growth, and reproduction of the eight dominant plant species. I then tested whether the phenological development of these species was controlled by snowmelt date or by temperature (in particular growing degree days, GDD). In order to expand our understanding of plant sensitivity to snowmelt timing, I explored whether the response patterns can be generalized with regard to the temporal niche of each species. Differences in the phenology between treatments were only found for the first stages of the phenological development (=phenophases). The earlier the temporal niche (i.e., the sooner after snowmelt a species develops) the more its phenology was sensitive to snowmelt. Later phenophases were mostly controlled by GDD, especially in late-developing species. In no species did an earlier snowmelt and a longer growing season directly enhance plant fitness or fecundity, in spite of the changes in the timing of plant development. In conclusion, the temporal niche of a species’ phenological development could be a predictor of its response to snowmelt timing. However, only the first phenophases were susceptible to changes in snowmelt, and no short-term effects on plant fitness were found.     

日光诱导叶绿素荧光对亚热带常绿针叶林物候的追踪

植被物候期(春季返青和秋季衰老)是表征生物响应和陆地碳循环的基础信息。由于常绿针叶林冠层绿度的季节变动较弱,遥感提取常绿针叶林的物候信息存在着较大的不确定性,是目前区域物候监测中的难点。利用MODIS植被指数(归一化植被指数NDVI和增强型植被指数EVI)、GOME-2日光诱导叶绿素荧光(SIF)和通量数据(总初级生产力GPP)估算2007—2011年亚热带常绿针叶林物候期,用来比较三类遥感指数估算常绿针叶林物候的差异。结果表明:基于表征光合作用物候的通量GPP数据估算得到5年内亚热带常绿针叶林生长季开始时间(SOS_(GPP))为第63天,生长季结束时间(EOS_(GPP))为第324天,生长季长度为272天;基于反映植被光合作用特征的SIF曲线获得物候信息要滞后GPP物候期,其中生长季开始时间滞后19天,生长季结束时间滞后2天;基于传统植被指数NDVI和EVI的物候期滞后GPP物候期的时间要大于SIF滞后期,其中植被指数SOS滞后SOS_(GPP)31天,植被指数EOS滞后EOS_(GPP)10—17天。虽然基于3种遥感指数估算的春季和秋季物候都滞后于通量GPP的物候期,但是卫星SIF的物候信息能够更好地捕捉常绿针叶林的生长阶段。同时,春季温度是影响森林生长季开始时间的最重要因素;秋季水分和辐射是影响生长季结束时间的关键因素。由此可见,SIF估算的亚热带常绿针叶林的春季和秋季物候的滞后时间要短于传统植被指数,能更好地追踪常绿林光合作用的季节性,为深入研究陆地生态系统碳循环及其对气候变化的响应提供重要的基础。     

季节性雪被变化对森林凋落物分解及土壤氮动态的影响

全球气候变化引发的雪被格局变化将深刻影响植被的凋落物分解、陆地生态系统的土壤养分循环等过程.森林是陆地生态系统的主体,在全球生物地球化学循环中起着不可替代的作用.本研究综述了季节性雪被变化对森林凋落物分解及土壤氮动态的影响.全球气候变化情景下季节性雪被表现出因地域而异的增加或减少的变化格局,一方面通过改变环境温湿度、凋落物质量、分解者动态等直接影响分解过程,另一方面通过改变森林群落结构、植被物候、土壤养分等间接地作用于凋落物分解.同时,季节性雪被通过影响氮富集作用、雪被下土壤温湿度、冻融循环、森林群落、雪下动物和微生物等相关因子而改变森林土壤氮循环.本领域未来应开展的研究是: 1) 全面考虑全球气候变化情景下季节性雪被格局的变异性,开展不同季节性雪被格局变化的模拟研究;2) 开展季节性雪被融雪水淋溶作用对森林凋落物分解和土壤氮动态的影响研究;3) 阐明不同生态系统和气候带中季节性雪被格局变化对森林凋落物分解过程和土壤氮动态的驱动机制研究;4) 量化季节性雪被变化对森林凋落物分解和土壤氮动态在雪被覆盖期的瞬时影响和无雪期的延续影响,为阐明和模型预测陆地生态系统生物地球化学循环对全球气候变化的响应提供理论基础和数据支持.     

Applying machine learning based on multiscale classifiers to detect remote phenology patterns in Cerrado savanna trees

Plant phenology is one of the most reliable indicators of species responses to global climate change, motivating the development of new technologies for phenological monitoring. Digital cameras or near remote systems have been efficiently applied as multi-channel imaging sensors, where leaf color information is extracted from the RGB (Red, Green, and Blue) color channels, and the changes in green levels are used to infer leafing patterns of plant species. In this scenario, texture information is a great ally for image analysis that has been little used in phenology studies. We monitored leaf-changing patterns of Cerrado savanna vegetation by taking daily digital images. We extract RGB channels from the digital images and correlate them with phenological changes. Additionally, we benefit from the inclusion of textural metrics for quantifying spatial heterogeneity. Our first goals are: (1) to test if color change information is able to characterize the phenological pattern of a group of species; (2) to test if the temporal variation in image texture is useful to distinguish plant species; and (3) to test if individuals from the same species may be automatically identified using digital images. In this paper, we present a machine learning approach based on multiscale classifiers to detect phenological patterns in the digital images. Our results indicate that: (1) extreme hours (morning and afternoon) are the best for identifying plant species; (2) different plant species present a different behavior with respect to the color change information; and (3) texture variation along temporal images is promising information for capturing phenological patterns. Based on those results, we suggest that individuals from the same species and functional group might be identified using digital images, and introduce a new tool to help phenology experts in the identification of new individuals from the same species in the image and their location on the ground.     

Greater phenological sensitivity to temperature on higher Scottish mountains: new insights from remote sensing

Mountain plants are considered among the species most vulnerable to climate change, especially at high latitudes where there is little potential for poleward or uphill dispersal. Satellite monitoring can reveal spatiotemporal variation in vegetation activity, offering a largely unexploited potential for studying responses of montane ecosystems to temperature and predicting phenological shifts driven by climate change. Here, a novel remote‐sensing phenology approach is developed that advances existing techniques by considering variation in vegetation activity across the whole year, rather than just focusing on event dates (e.g. start and end of season). Time series of two vegetation indices (VI), normalized difference VI (NDVI) and enhanced VI (EVI) were obtained from the moderate resolution imaging spectroradiometer MODIS satellite for 2786 Scottish mountain summits (600–1344 m elevation) in the years 2000–2011. NDVI and EVI time series were temporally interpolated to derive values on the first day of each month, for comparison with gridded monthly temperatures from the preceding period. These were regressed against temperature in the previous months, elevation and their interaction, showing significant variation in temperature sensitivity between months. Warm years were associated with high NDVI and EVI in spring and summer, whereas there was little effect of temperature in autumn and a negative effect in winter. Elevation was shown to mediate phenological change via a magnification of temperature responses on the highest mountains. Together, these predict that climate change will drive substantial changes in mountain summit phenology, especially by advancing spring growth at high elevations. The phenological plasticity underlying these temperature responses may allow long‐lived alpine plants to acclimate to warmer temperatures. Conversely, longer growing seasons may facilitate colonization and competitive exclusion by species currently restricted to lower elevations. In either case, these results show previously unreported seasonal and elevational variation in the temperature sensitivity of mountain vegetation activity.     

Public Internet‐connected cameras used as a cross‐continental ground‐based plant phenology monitoring system

Plant phenology is highly sensitive to changes in environmental conditions and can vary widely across landscapes. Current observation methods are either manual for small‐scale, high precision measurements or by satellite remote sensing for large‐scale, low spatial resolution measurement. The development of inexpensive approaches is necessary to advance large scale, high precision phenology monitoring. The use of publicly available, Internet‐connected cameras, often associated with airports, national parks, and roadway conditions, for detecting and monitoring plant phenology at a continental scale can augment existing ground and satellite‐based methodologies. We collected twice‐daily images from over 1100 georeferenced public cameras across North America from February 2008 to 2009. Using a test subset of these cameras, we compared modeled spring ‘green‐up’ with that from co‐occurring remote sensing products. Although varying image exposure and color correction introduced noise to camera measurements, we were able to correlate spring green‐up across North America with visual validation from images and detect a latitudinal trend. Public cameras had an equivalent or higher ability to detect spring compared with satellite‐based data for corresponding locations, with fewer numbers of poor quality days, shorter continuous bad data days, and significantly lower errors of spring estimates. Manual image segmentation into deciduous, evergreen, and understory vegetation allowed detection of spring and fall onset for multiple vegetation types. Additional advantages of a public camera‐based monitoring system include frequent image capture (subdaily) and the potential to detect quantitative responses to environmental changes in organisms, species, and communities. Public cameras represent a relatively untapped and freely available resource for supporting large‐scale ecological and environmental monitoring.     

Phenological responses to small-scale spatial variation in snowmelt timing reveal compensatory and conservative strategies in subarctic-alpine plants

Background: In tundra ecosystems, the adjustment of phenological events, such as bud burst, to snowmelt timing is crucial to the climatic adaptation of plants. Natural small-scale variations in microclimate potentially enable plant populations to persist in a changing climate.

Aims: To assess how plant phenology responds to natural differences in snowmelt timing.

Methods: We observed the timing of eight vegetative and reproductive phenophases in seven dwarf-shrub species in relation to differences in snowmelt timing on a small spatial scale in an alpine environment in subarctic Finland.

Results: Some species and phenophases showed accelerated development with later snowmelt, thus providing full or partial compensation for the shorter snow-free period. Full compensation resulted in synchronous occurrence of phenophases across the snowmelt gradient. In other species, there was no acceleration of development. The timing of phenophases varied between two consecutive years and two opposing mountain slope aspects.

Conclusions: The results have shown three distinct patterns in the timing of phenophases in relation to snowmelt and suggest alternative strategies for adaptation to snowmelt timing. These strategies potentially apply to other species and tundra ecosystems and provide a framework, enabling one to compare and generalise phenological responses to snowmelt timing under different future climate scenarios.     

Different temperature perception in high‐elevation plants: new insight into phenological development and implications for climate change in the alpine tundra

In alpine habitats, predicted warmer and longer growing seasons will influence plant phenology, with important implications for species adaptation and vegetation dynamics. However, little is known on the temperature sensitivity of different phenophases and on the characteristics allowing phenological variation among and within species. By integrating interannual micro‐climatic variability with experimental warming, we explored how the phenology of three alpine species is influenced by temperature and what mechanisms underlie intra‐ and inter‐specific phenological differences. The present study demonstrated that alpine plants have different temperature responses during their reproductive cycle, do not have constant thermal thresholds and heat‐use efficiencies to achieve the seed dispersal stage and can change their temperature sensitivity to flower along snowmelt gradients. In addition, the length of the reproductive cycle, which proved to be species‐specific under experimental warming, does not seem to be the only life‐history trait under selective pressure due to the short‐length of the snow‐free period. In a warming climate scenario, the phenology of sexual reproduction will be considerably altered, and alpine plants may be subjected to changes in population dynamics driven by altered perception of environmental cues appropriate for coordinating the timing of key life‐history events.     

Using phenological cameras to track the green up in a cerrado savanna and its on-the-ground validation

Plant phenology has gained new importance in the context of global change research, stimulating the development of novel technologies for phenological observations. Regular digital cameras have been effectively used as three-channel imaging sensors, providing measures of leaf color change or phenological shifts in plants. We monitored a species rich Brazilian cerrado savanna to assess the reliability of digital images to detect leaf-changing patterns. Analysis was conducted by extracting color information from selected parts of the image named regions of interest (ROIs). We aimed to answer the following questions: (i) Do digital cameras capture leaf changes in cerrado savanna vegetation? (ii) Can we detect differences in phenological changes among species crowns and the cerrado community? (iii) Is the greening pattern detected for each species by digital camera validated by our on-the-ground leafing phenology (direct observation of tree leaf changes)? We analyzed daily sequences of five images per hour, taken from 6:00 to 18:00 h, recorded during the cerrado main leaf flushing season. We defined 24 ROIs in the original digital image, including total or partial regions and crowns of six plant species. Our results indicated that: (i) for the studied period, single plant species ROIs were more sensitive to changes in relative green values than the community ROIs, (ii) three leaf strategies could be depicted from the species' ROI patterns of green color change, and (iii) the greening patterns and leaf functional groups were validated by our on-the-ground phenology. We concluded that digital cameras are reliable tools to monitor high diverse tropical seasonal vegetation and it is sensitive to inter-species differences of leafing patterns.     

Spring phenology rather than climate dominates the trends in peak of growing season in the Northern Hemisphere

Shifts in plant phenology regulate ecosystem structure and function, which feeds back to the climate system. However, drivers for the peak of growing season (POS) in seasonal dynamics of terrestrial ecosystems remain unclear. Here, spatial–temporal patterns of POS dynamics were analyzed by solar-induced chlorophyll fluorescence (SIF) and vegetation index in the Northern Hemisphere over the past two decades from 2001 to 2020. Overall, a slow advanced POS was observed in the Northern Hemisphere, while a delayed POS distributed mainly in northeastern North America. Trends of POS were driven by the start of growing season (SOS) rather than pre-POS climate both at hemisphere and biome scale. The effect of SOS on the trends in POS was the strongest in shrublands while the weakest in evergreen broad-leaved forest. These findings highlight the crucial role of biological rhythms rather than climatic factors in exploring seasonal carbon dynamics and global carbon balance.     

Shrub expansion modulates belowground impacts of changing snow conditions in alpine grasslands

Climate change is disproportionately impacting mountain ecosystems, leading to large reductions in winter snow cover, earlier spring snowmelt and widespread shrub expansion into alpine grasslands. Yet, the combined effects of shrub expansion and changing snow conditions on abiotic and biotic soil properties remains poorly understood. We used complementary field experiments to show that reduced snow cover and earlier snowmelt have effects on soil microbial communities and functioning that persist into summer. However, ericaceous shrub expansion modulates a number of these impacts and has stronger belowground effects than changing snow conditions. Ericaceous shrub expansion did not alter snow depth or snowmelt timing but did increase the abundance of ericoid mycorrhizal fungi and oligotrophic bacteria, which was linked to decreased soil respiration and nitrogen availability. Our findings suggest that changing winter snow conditions have cross-seasonal impacts on soil properties, but shifts in vegetation can modulate belowground effects of future alpine climate change.     

Land Surface Phenology in the Tropics: The Role of Climate and Topography in a Snow-Free Mountain

Leaf phenology represents a major temporal component of ecosystem functioning, and understanding the drivers of seasonal variation in phenology is essential to understand plant responses to climate change. We assessed the patterns and drivers of land surface phenology, a proxy for leafing phenology, for the meridional Espinhaço Range, a South American tropical mountain comprising a mosaic of savannas, dry woodlands, montane vegetation and moist forests. We used a 14-year time series of MODIS/NDVI satellite images, acquired between 2001 and 2015, and extracted phenological indicators using the TIMESAT algorithm. We obtained precipitation data from the Tropical Rainfall Measuring Mission, land surface temperature from the MODIS MOD11A2 product, and cloud cover frequency from the MODIS MOD09GA product. We also calculated the topographic wetness index and simulated clear-sky radiation budgets based on the SRTM elevation model. The relationship between phenology and environmental drivers was assessed using general linear models. Temporal displacement in the start date of the annual growth season was more evident than variations in season length among vegetation types, indicating a possible temporal separation in the use of resources. Season length was inversely proportional to elevation, decreasing 1.58 days per 100 m. Green-up and senescence rates were faster where annual temperature amplitude was higher. We found that water and light availability, modulated by topography, are the most likely drivers of land surface phenology in the region, determining the start, end and length of the growing season. Temperature had an important role in determining the rates of leaf development and the strength of vegetation seasonality, suggesting that tropical vegetation is also sensitive to latitudinal temperature changes, regardless of the elevational gradient. Our work improves the current understanding of phenological strategies in the seasonal tropics and emphasizes the importance of topography in shaping light and water availability for leaf development in snow-free mountains.     

基于数字相机的冬小麦物候和碳交换监测

利用数字相机自动、连续监测植被冠层物候变化,逐渐引起人们的广泛关注。依托中国陆地生态系统通量观测研究网络(ChinaFLUX),探讨了数字相机在监测冬小麦生长状况及生态系统碳交换方面的作用,得到如下结果:(1)利用数字相机图像提取的比值绿度指数G/R能较好地反映冬小麦冠层物候变化,通过分析比值绿度指数G/R的时间序列,得到了较为准确的冬小麦关键生育日期(与人工观测数据比较,误差<3 d),表明数字相机可以作为物候监测的一种有效手段;(2)数字相机图像获取的比值绿度指数能较好地模拟冬小麦总生态系统碳交换量GEE,R2为0.66,叶片最大光合同化速率与比值绿度指数G/R变化趋势基本一致。表明利用数字相机技术在一定程度上能够表征作物生理生态过程。从而为我国开展不同陆地生态系统自动连续物候监测,深入研究不同生态系统物候和碳循环的关系提供支持。     

Comparing phenocam color indices with phenological observations of black spruce in the boreal forest

Bud phenology identifies the growing period of trees and determines the pattern of mass and energy exchanges between forest and atmosphere over time and space. Canopy color metrics derived from phenocams have been widely used to investigate tree phenology. However, it remains unclear which color-based index better tracks the seasonal variations of tree phenology in evergreen forest ecosystems. Herein, we compared four color metrics (red chromatic coordinate (RCC), green chromatic coordinate (GCC), vegetation contrast index (VCI) and excess green index (ExG)) derived from phenocam images with bud phenological phases recorded in black spruce [Picea mariana (Mill.) B.S·P] during 2017–2020 at a boreal forest site in Quebec, Canada. Canopy redness (RCC) and greenness (GCC, ExG, and VCI) showed a bimodal and bell-shaped seasonal pattern, respectively. The phases of bud burst and bud set lasted from end-May to end-June and from mid-July to end-September, respectively. The neural network model indicated that GCC had the best predictive ability in capturing the sequential phases of bud phenology. Bud phenological phases predicted by GCC showed the highest correlation with actual bud phenological phases among four indices, with R² above 0.9 and RMSE lower than 0.5. Overall, color indices performed better when representing bud burst than bud set. Our findings improve the efficiency and confidence of the phenocam greenness index to characterize the growing season of evergreen forests.     

Small-scale plant species distribution in snowbeds and its sensitivity to climate change

Alpine snowbeds are characterized by a long-lasting snow cover and low soil temperature during the growing season. Both these key abiotic factors controlling plant life in snowbeds are sensitive to anthropogenic climate change and will alter the environmental conditions in snowbeds to a considerable extent until the end of this century. In order to name winners and losers of climate change among the plant species inhabiting snowbeds, we analyzed the small-scale species distribution along the snowmelt and soil temperature gradients within alpine snowbeds in the Swiss Alps. The results show that the date of snowmelt and soil temperature were relevant abiotic factors for small-scale vegetation patterns within alpine snowbed communities. Species richness in snowbeds was reduced to about 50% along the environmental gradients towards later snowmelt date or lower daily maximum temperature. Furthermore, the occurrence pattern of the species along the snowmelt gradient allowed the establishment of five species categories with different predictions of their distribution in a warmer world. The dominants increased their relative cover with later snowmelt date and will, therefore, lose abundance due to climate change, but resist complete disappearance from the snowbeds. The indifferents and the transients increased in species number and relative cover with higher temperature and will profit from climate warming. The snowbed specialists will be the most suffering species due to the loss of their habitats as a consequence of earlier snowmelt dates in the future and will be replaced by the avoiders of late-snowmelt sites. These forthcoming profiteers will take advantage from an increasing number of suitable habitats due to an earlier start of the growing season and increased temperature. Therefore, the characteristic snowbed vegetation will change to a vegetation unit dominated by alpine grassland species. The study highlights the vulnerability of the established snowbed vegetation to climate change and requires further studies particularly about the role of biotic interactions in the predicted invasion and replacement process.     

Intrinsic and extrinsic factors acting on the reproductive process in alpine‐snowbed plants: roles of phenology,biological interaction,and breeding system

Pollinator activity and competition for pollinators lead to quantitative and qualitative pollen limitations on seed production and affect the reproductive success of plant species, depending on their breeding system (e.g., self‐compatibility and heterospecific compatibility) and genetic load (e.g., inbreeding depression and hybrid inviability). In alpine ecosystems, snowmelt regimes determine the distribution and phenology of plant communities. Plant species growing widely along a snowmelt gradient often grow with different species among local populations. Their pollinators also vary in their abundance, activity, and behavior during the season. These variations may modify plant–pollinator and plant–plant interactions. We integrated a series of our studies on the alpine dwarf shrub, Phyllodoce aleutica (Ericaceae), to elucidate the full set of intrinsic (species‐specific breeding system) and extrinsic factors (snow condition, pollinator activity, and interspecific competition) acting on their reproductive process. Seasonality of pollinator activity led to quantitative pollen limitation in the early‐blooming populations, whereas in the late‐blooming populations, high pollinator activity ensured pollination service, but interspecific competition for pollinators led to qualitative and quantitative pollen limitation in less competitive species. However, negative effects of illegitimate pollen receipt on seed‐set success might be reduced when cryptic incompatibility systems (i.e., outcross pollen grains took priority over self‐ and heterospecific pollen grains) could effectively prevent ovule and seed discounting. Our studies highlight the importance of species‐specific responses of plant reproduction to changing pollinator availability along environmental gradients to understand the general features of pollination networks in alpine ecosystems.     

Assessing the use of camera-based indices for characterizing canopy phenology in relation to gross primary production in a deciduous broad-leaved and an evergreen coniferous forest in Japan

Recent studies have reported that seasonal variation in camera-based indices that are calculated from the digital numbers of the red, green, and blue bands (RGB_DN) recorded by digital cameras agrees well with the seasonal change in gross primary production (GPP) observed by tower flux measurements. These findings suggest that it may be possible to use camera-based indices to estimate the temporal and spatial distributions of photosynthetic productivity from the relationship between RGB_DN and GPP. To examine this possibility, we need to investigate the characteristics of seasonal variation in three camera-based indices (green excess index [GE], green chromatic coordinate [rG], and HUE) and the robustness of the relationship between these indices and tower flux-based GPP and how it differs among ecosystems. Here, at a daily time step over multiple years in a deciduous broad-leaved and an evergreen coniferous forest, we examined the relationships between canopy phenology assessed by using the three indices and GPP determined from tower CO₂ flux observations, and we compared the camera-based indices with the corresponding spectra-based indices estimated by a spectroradiometer system. We found that (1) the three camera-based indices and GPP showed clear seasonal patterns in both forests; (2) the amplitude of the seasonal variation in the three camera-based indices was smaller in the evergreen coniferous forest than in the deciduous broad-leaved forest; (3) the seasonal variation in the three camera-based indices corresponded well to seasonal changes in potential photosynthetic activity (GPP on sunny days); (4) the relationship between the three camera-based indices and GPP appeared to have different characteristics at different phenological stages; and (5) the camera-based and spectra-based HUE indices showed a clear relationship under sunny conditions in both forests. Our results suggest that it might be feasible for ecologists to establish comprehensive networks for long-term monitoring of potential photosynthetic capacity from regional to global scales by linking satellite-based, in situ spectra-based, and in situ camera-based indices.     

Drought footprint on European ecosystems between 1999 and 2010 assessed by remotely sensed vegetation phenology and productivity

Drought affects more people than any other natural disaster but there is little understanding of how ecosystems react to droughts. This study jointly analyzed spatio‐temporal changes of drought patterns with vegetation phenology and productivity changes between 1999 and 2010 in major European bioclimatic zones. The Standardized Precipitation and Evapotranspiration Index (SPEI) was used as drought indicator whereas changes in growing season length and vegetation productivity were assessed using remote sensing time‐series of Normalized Difference Vegetation Index (NDVI). Drought spatio‐temporal variability was analyzed using a Principal Component Analysis, leading to the identification of four major drought events between 1999 and 2010 in Europe. Correspondence Analysis showed that at the continental scale the productivity and phenology reacted differently to the identified drought events depending on ecosystem and land cover. Northern and Mediterranean ecosystems proved to be more resilient to droughts in terms of vegetation phenology and productivity developments. Western Atlantic regions and Eastern Europe showed strong agglomerations of decreased productivity and shorter vegetation growing season length, indicating that these ecosystems did not buffer the effects of drought well. In a climate change perspective, increase in drought frequency or intensity may result in larger impacts over these ecosystems, thus management and adaptation strategies should be strengthened in these areas of concerns.     

Impacts of snow cover duration on vegetation spring phenology over the Tibetan Plateau

Aims Snow cover occupies large percentage of land surface in Tibetan Plateau. Snow cover duration (SCD) during non-growing seasons plays a critical role in regulating alpine vegetation’s phenology by affecting the energy budgets of land surface and soil moisture conditions. Different period’s snow cover during non-growing season may have distinct effect on the vegetation’s phenology. Start of season (SOS) has been observed advanced under the ongoing climate change in the plateau, but it still remains unclear how the SCD alters the SOS. This study attempts to answer the following questions: (i) What is the pattern of spatial and temporal variations for SCD and grassland SOS? (ii) Which period’s SCD plays a critical role in grassland’s SOS?